Network traffic classification

ABSTRACT

A computer implemented method and system comprising receiving a data packet from a network source, extracting source and destination data from the received data packet, determining a user from the extracted source and destination data from the received data packet. If a label does not exist for the extracted source and destination data from the received data packet, creating a label for the data packet, the label comprising the extracted source data and historic source data for the determined user, calling a chaotic function with the label for the received data packet. If the chaotic function returns false, calling an alternative function for an output with the label for the received data packet. If the chaotic function returns true, capturing the output of the chaotic function, and updating the label with the output of the chaotic function or with the output of the alternative function.

BACKGROUND

The present invention relates to a method, system and computer programproduct for performing the classification of network traffic. Networkoperators that handle network traffic between, for example a mobilephone and a web server, classify the network traffic in order to obtaininformation about the use of their network.

SUMMARY

According to an aspect of the present invention, a computer implementedmethod, includes receiving a data packet from a network source;extracting source and destination data from the received data packet;and determining a user from the extracted source and destination datafrom the received data packet. The method includes creating a label forthe data packet, in response to a determination that the label does notexist for the extracted source and destination data from the receiveddata packet. The label including the extracted source data and historicsource data for the determined user. The method includes calling achaotic function with the label for the received data packet. The methodfurther includes calling an alternative function for an output with thelabel for the received data packet, in response to the chaotic functionbeing returned false. The method includes capturing the output of thechaotic function, in response to the chaotic function being returnedtrue. The label is updated with the output of the chaotic function orwith the output of the alternative function.

In another aspect according to the present invention, a system forcontrolling network traffic includes: a computer system comprising: acomputer processor, computer-readable storage media, and programinstructions stored on the computer-readable storage media, the programinstructions being executable by the processor to cause the computersystem to: receive a data packet from a network source; extract sourceand destination data from the received data packet; determine a userfrom the extracted source and destination data from the received datapacket; create a label for the data packet, in response to adetermination that the label does not exist for the extracted source anddestination data from the received data packet, the label including theextracted source data and historic source data for the determined user;call a chaotic function with the label for the received data packet;call an alternative function for an output with the label for thereceived data packet, in response to the chaotic function being returnedfalse; capture the output of the chaotic function, in response to thechaotic function being returned true; and update the label with theoutput of the chaotic function or with the output of the alternativefunction.

In another aspect according to the present invention, a computer programproduct for controlling network traffic comprises a computer readablestorage medium having program instructions embodied therewith, theprogram instructions executable by a processor to cause the processor toperform the program instructions comprising:

Receiving a data packet from a network source; extracting source anddestination data from the received data packet; determining a user fromthe extracted source and destination data from the received data packet;creating a label for the data packet, in response to a determinationthat the label does not exist for the extracted source and destinationdata from the received data packet, the label including the extractedsource data and historic source data for the determined user; calling achaotic function with the label for the received data packet; calling analternative function for an output with the label for the received datapacket, in response to the chaotic function being returned false;capturing the output of the chaotic function, in response to the chaoticfunction being returned true; and updating the label with the output ofthe chaotic function or with the output of the alternative function.

BRIEF DESCRIPTION OF THE DRAWINGS

Preferred embodiments of the present invention will now be described, byway of example only, with reference to the following drawings,hereinbelow.

FIG. 1 is a schematic diagram of a client and a server communicatingover a wide area network in accordance with a preferred embodiment.

FIG. 2 is a flowchart of a method of classifying a network packet inaccordance with a preferred embodiment.

FIG. 3 is a schematic diagram of a server in accordance with a preferredembodiment.

FIG. 4 is a schematic diagram of a mobile phone and a servercommunicating over a wide area network in accordance with a preferredembodiment.

FIG. 5 is a block diagram of a computer system according to oneembodiment of the disclosure.

DETAILED DESCRIPTION

FIG. 1 shows an appliance 10, which is embodied as a network collector,that is monitoring network traffic, shown here as a data packet 12 thatis travelling through a wide area network 14 such as the Internetbetween a client device 16 and a server 18. Here, the client device 16is a desktop PC. The main problem of network traffic classification isthe large amount of network flow on fixed and mobile networks, such asthe Internet, that is delivered through fixed line telecoms and mobilephone networks. The appliance 10 is not capable of analysing all of thenetwork flow without vastly increasing processing load (CPU) and thepower consumption. Therefore the appliance 10 is operated to efficientlyclassify network packets 12 by using a faster process that has an errorrate that is acceptable in the context of the end result that isachieved.

With this method the appliance 10 is operated to discard network flowsby using a source port of a user flow determined from the data packet 12and a chaotic function that will compute which flows will be discardedand evaluated by the chaotic function. Due to this effect, the networkcollector 10 will boost the performance and, as a consequence of thiseffect, more traffic is analysed by the network collector 10. In orderto boost the performance and the capabilities of the network collector10, the collector 10 operates a method for discarding TCP/UDP(Transmission Control Protocol (TCP) and User Datagram Protocol (UDP)user network flows that uses a chaotic function based on the sourceport. Information is harvested from the data packet 12 and thisharvested data is used to obtain the source port data and otherinformation that is used by the network collector 10 to make theclassification.

The steps of the process, from the point of view of the appliance 10,which operates as a network collector 10 are as follows. Firstly, thenetwork collector 10 receives a packet 12 from a network device (such asan ethernet device). Then the network collector 10 extracts source anddestination data in the form of a five-tuple from the packet 12, whichcomprises information about the IP source, source port, protocol, IPdestination and destination port. From a user data field in the packet12, by using the IP source, the collector 10 takes the user informationassociated with the user. If the network flow is not currently labelled,the collector 10 extracts from the flow and the user, the source portand a vector with the last used ports of the given user.

The network collector 10 will then call a chaotic function (such as aLorenz attractor) using as arguments the source port of the flow and thecreated vector of the last used ports. If the chaotic function returnsfalse on the update variable, this means that the algorithm being run bythe network collector 10 must continue by analysing the network flowusing standard methods such as pattern matching using ports and IPaddresses and other data. If the chaotic function returns true, then thelabel has a value and the flow will be matching to this value. In thiscase, when the chaotic function returns a true value, then the CPU andmemory consumption are reduced as a result of classifying the packetwithout recourse to a resource intensive method such as patternmatching. The flow is matched with the label, and the vector of the useris updated in order to have the new values added to the vector.

The network collector 10 classifies data traffic using the chaoticfunction in order to understand the nature of the network traffic.Classification of the data means identifying the application thatgenerates the flow or conversation defined by one or more data packets.For example, an end user of a device 16 may be using an application suchas an instant messenger. This application, when connected to theInternet, generates network traffic to messaging servers and/or otherdestinations. The conversations (flows) that this application generatesare classified by the network collector 10 in order to identify theapplication and to generate relevant information for network operators.The classification does not attempt to predict the next user action, theprocess executed by the network collector 10 uses chaos theory toclassify network traffic by using the source ports of the user as aninput for the chaotic function. The algorithm executed by the collector10 can be summarised according to the pseudo-code written below:

packet = getPacket( ) flow = getFlowFromPacket(packet) user =getUserData(flow) if flow.isNotLabel( ):  sport = flow.getSourcePort( )# int  vport = user.getLastUsedPorts( ) # list( )  update, label =chaoticCheaperMethod(sport,vport)  if not update:   # The chaoticfunction returns false, so the flow must be label   # using standard dpitechniques (pattern matching or port/ip matching)   label =analyseTheFlowByExpensiveMethods(flow)  endif  flow.setLabel(label) #the flow is marked as label also, step 8 user.updateLastUsedPorts(sport,label) endif

The process defined by the pseudo-code listed above takes the packetthat is being classified and if the packet is not currently labelled,then a call is made to a chaotic function such as a Lorenz attractor,using the source port data and a vector created from the last used portsof the user as the arguments for the chaotic function, which will returntrue (with an output) or false (without an output). If the chaoticfunction does return an output, then this can be used to update thelabel by extending the label with the output returned. If the chaoticfunction does not return a label, then an alternative method ofclassifying the packet from the information available will be used.

FIG. 2 shows a flowchart that summarises the methodology of the networkcollector 10, which is executing an algorithm according to the processsteps defined in the flowchart of FIG. 2. The algorithm defines acomputer implemented method 100 that comprises at step S2.1 receiving adata packet from a network source, at step S2.2 extracting source anddestination data from the received data packet, and at step S2.3determining a user from the extracted source and destination data fromthe received data packet. A check is then made to see if the currentflow is labelled and if a label does not exist for the received datapacket, than at step S2.4 there is created a label for the data packet,the label comprising source data and historic source data for thedetermined user.

At step S2.5 the algorithm calls a chaotic function with the label forthe received data packet. A check is then made to see if an update canbe made, which will be the case id the chaotic function returned a trueoutput. If the chaotic function returns false, the method continues atstep S2.6 by calling an alternative function for an output with thelabel for the received data packet. If the chaotic function returnstrue, at step S2.7 there is captured the output of the chaotic function,and at step S2.8 the method terminates by updating the label with theoutput of the chaotic function or with the output of the alternativefunction.

In this way, the received packet is classified with a label if such alabel does not already exist for the data flow that is defined by thedata packet. In step S2.2 the extracting of source and destination datafrom the received data packet comprises extracting an IP source, sourceport, IP destination and destination port from the received data packet.In step S2.4 the creating of a label for the data packet, where thelabel comprising source data and historic source data for the determineduser, comprises creating a label that comprises the source port and avector comprising the last used ports of the determined user. In stepS2.8 the updating of the label with the output of the chaotic functionor with the output of the alternative function comprises the action ofextending the vector with the source port and the output of the chaoticfunction or the output of the alternative function.

FIG. 3 shows the appliance embodied as a network collector 10 in moredetail as a system with components according to one embodiment, and thusthe appliance/network collector 10 is also referred to as a systemaccording to one embodiment of the network collector or just as asystem. The system of the network collector 10 includes a processor 20,a storage device 22 that is connected to the processor 20 and a networkinterface 24 that is also connected to the processor 20. A computerreadable medium 26 (a CD-ROM) is provided that comprises a computerprogram product. The system includes a drive 28 which is able to acceptthe CD-ROM 26. The computer program product comprises a set ofinstructions that are used to control the operation of the processor 20.The system operates by receiving data packets via the network interface24 which are then examined by the processor 20 according to thealgorithm detailed in FIG. 2 above. Results are stored in the storagedevice 22.

The system can be embodied as a server that is connected to theInternet. Network traffic can be monitored as the traffic is routedthrough one or more routing servers that are routing data packetsthrough the Internet to their destination. The network collector 10accesses data packets and extracts source and destination data from thedata packets which is then used to label each data packet, if no suchlabel already exists for the respective data packet. The label iscreated from the extracted information from the respective data packet.Source port and destination port data can be used to create the labelfor the specific data packet.

A chaotic function is called with the label in order to attempt toclassify the data packet by determining the next port that the user willcall. A chaotic function is used on the understanding that the functionwill not always be able to return a valid output, but that this is aprice worth paying in order to use a lower cost option in terms ofprocessor and time resources. If the chaotic function is unable toreturn a valid output then an alternative function will be used toclassify the data packet that is currently being considered. Thealternative function, in a preferred embodiment, uses pattern matchingin order to classify the packet.

An example where the chaotic function returns “True” as the output isbased on the following data that has been extracted from a received datapacket by the network collector:

-   sport=509734-   vport=((512000,“Facebook®”),(523100,“Facebook®”),(532198,“Facebook®”))

Source and destination data has been extracted from the received packetand a label is created that comprises the source port (sport) and avector (vport) created from the last used destination ports of the userin question. In this example, three destination ports have beendetermined with a classification of the destination, in this case allthree destination ports being for the website Facebook®. The vport is atwo-dimensional vector, here comprised of three x,y co-ordinates. Thesport and vport are the outputs of step S2.4 of FIG. 2. The label isthen used as the call to the chaotic function being used as per thefollowing pseudo-code:

-   update, label=chaoticCheaperMethod(sport,vport) # Update=True,-   label=“Facebook®”-   flow.setLabel(label) # Facebook®-   user.updateLastUserPorts(sport,label)#-   vport=((512000,“Facebook®”),(523100, “Facebook®”),(532198,    “Facebook®”), (509734, “Facebook®”))

The chaotic function being used has returned a valid output “Facebook®”and has therefore returned a “True” output. The label for the packet cantherefore be extended with the generated classification and as can beseen in the final two lines of the pseudo-code, the vector defining thedestination activity of the user has been extended by the addition of anew x,y co-ordinate, which is the sport plus the output returned by thechaotic function being used, here a Lorenz attractor. This is defined bythe line of pseudo-code “user.updateLastUserPorts(sport,label)”.

This processing of a data packet that has been received by the networkcollector 10 is carried out by the processor 20 under the control of thecomputer program product provided on the CD-ROM 26, as shown in FIG. 3.The processor 20 executes the algorithm shown in the flowchart of FIG. 2and, if there is no label for the data packet (which is determined withreference to the user data extracted that has been extracted from thedata packet) then the new label is generated and used to call thechaotic function. The chaotic function provides a valid output that isthen used to extend the label for the packet in question.

A second example in which the chaotic function returns “False” will nowbe discussed, which is based upon the following data extracted from asecond data packet. In this example, the source port and vector takenfrom the destination ports are as follows:

-   sport=509732-   vport=((502000,“Google®”),(523110,“Facebook®”),(532191,“Facebook®”))

The vector generated from the destination information comprises a vectorwith three x,y co-ordinates that define calls to Google® and then twiceto Facebook®. The pseudo-code continues as follows:

-   update, label=chaoticCheaperMethod(sport,vport) # Update=False,    label=“None” label=analyse(flow)-   flow.setLabel(label) # Twitter®    user.updateLastUserPorts(sport,label) # vport=((502000,    “Google®”),(523110, “Facebook®”),(532191, “Facebook®”),(509732,    “Twitter®”))

In this example, the chaotic function returns “False” so a standardclassification (an expensive) method is used for analyse the flow. Thisalternative function, such as regex pattern, ip/port matching returnsthe label=“Twitter®” and this is used to update the user's label for thepacket in question. In this example the chaotic function failed toreturn a valid output and therefore the processor 20 continued thealgorithm by calling an alternative function. The nature of thealternative function is not material, as long as the function uses asuitable technique that is able to return a prediction about the datapacket being classified.

A further example in which the chaotic function returns a “True” valueis further provided in which the extracted data from the received datapacket is as follows:

-   sport=509799-   vport=((502000,“Google®”),(523110,“Facebook®”),(532191,“Facebook®”),(509732,“Twitter®”))

In this example, the label generated in terms of the vector created fromthe last used destination ports of the specific user is a set of fourx,y co-ordinates that define visits to four websites in turn, Google®,Facebook® (twice) and finally Twitter®. The vport (the vector from thedestination ports) can be of any length and is generated from theavailable data relating to the data packet in question. The user isidentified from the data packet, and stored data for that user can beused to generate a list of the previously visited destination port. Thepseudo-code for the example continues as follows:

-   update, label=chaoticCheaperMethod(sport,vport) # Update=True,    label=“Twitter®”-   flow.setLabel(label) # Twitter®-   user.updateLastUserPorts(sport,label) # vport=((502000,    “Google®”),(523110, “Facebook®”),(532191, “Facebook®”),(509732,    “Twitter®”), (509799, “Twitter®”))

In this example, the chaotic function is able to return a valid outputand this is the label “Twitter®” and this label is used to extend thevector that is extended by the x,y coordinate of the sport and the labelgenerated by the chaotic function. In this way, the classification ofthe data packet is achieved and the label can be extended using thechaotic function and the label passed to the function that has beengenerated from the data extracted from the data packet.

FIG. 4 shows a further example of a device that is communicating overthe Internet 14 with a server 18. In this example, the device is amobile phone 30 that is able to access advanced Internet servicesthrough a wireless 3G service. The server 18 is running an instantmessaging application and a network provider in the communication chainis operating an appliance embodied as a network classification server 34(also referred to as a network classifier) that is able to access todata packets 12 that are being transmitted over the Internet to and fromthe mobile phone 30 and the server 18. The network operator could be themobile phone provider, who wishes to classify the data traffic that istravelling on their network.

The data packet 12 is available to the network classifier 34 to classifythe data packet 12, in terms of classifying the destination of the datapacket using a chaotic function in the first instance, and analternative function if the chaotic function is unable to classify thedata packet 12. In this example, the extracted data from the receiveddata packet 12 is as follows:

sport=10

vport=((1,“labelA”),(2,“labelB”),(8,“labelC”))

The chaotic function does not operate on the associated words. Thefunction operates by computing the next probable point (source port).The labels are associated to a number that is the source port of theuser. In this case, the sport is closer to the “labelC” because theassociated number is 8, and 10 is closer to 8 than 1 and 2 in thisexample, so if the chaotic function returns a true value from thesenumbers, then the output will be the “labelC”.

Thereby, the invention provides in one embodiment, a computerimplemented method comprising receiving a data packet from a networksource, extracting source and destination data from the received datapacket, and determining a user from the extracted source and destinationdata from the received data packet. If a label does not exist for theextracted source and destination data from the received data packet, alabel is created for the data packet. The label comprises the extractedsource data and historic source data for the determined user. The methodincludes calling a chaotic function with the label for the received datapacket. If the chaotic function returns false, the method calls analternative function for an output with the label for the received datapacket. If the chaotic function returns true, the method captures theoutput of the chaotic function. The method updates the label with theoutput of the chaotic function or with the output of the alternativefunction.

According to another embodiment of the present invention, a systemcomprises a processor arranged to receive a data packet from a networksource, extract source and destination data from the received datapacket, and determine a user from the extracted source and destinationdata from the received data packet. If a label does not exist for theextracted source and destination data from the received data packet, alabel is created for the data packet. The label comprising the extractedsource data and historic source data for the determined user. The systemcalls a chaotic function with the label for the received data packet. Ifthe chaotic function returns false, the system calls an alternativefunction for an output with the label for the received data packet. Ifthe chaotic function returns true, the system captures the output of thechaotic function, and updates the label with the output of the chaoticfunction or with the output of the alternative function.

According to another embodiment of the invention, there is provided acomputer program product for controlling a system for controllingnetwork traffic. The computer program product comprising a computerreadable storage medium having program instructions embodied therewith,the program instructions executable by a processor to cause theprocessor to receive a data packet from a network source, extract sourceand destination data from the received data packet, determine a userfrom the extracted source and destination data from the received datapacket. If a label does not exist for the extracted source anddestination data from the received data packet, a label is created forthe data packet. The label comprising the extracted source data andhistoric source data for the determined user. A chaotic function withthe label for the received data packet is called. If the chaoticfunction returns false, an alternative function is called for an outputwith the label for the received data packet. If the chaotic functionreturns true, the output of the chaotic function is captured, and thelabel is updated with the output of the chaotic function or with theoutput of the alternative function.

Referring to FIG. 5, according to one embodiment of the presentdisclosure, a computing system or computer system 1000 (previouslyintroduced and illustrated in FIG. 1) is described below in more detail.The computer system 1000 may also be considered a node of a plurality ofcomputers or nodes of a system. The computer system 1000 is illustrativeand is not intended to suggest any limitation as to the scope of use orfunctionality of embodiments of the invention described herein. Thecomputer system 1000 includes a computer 1010 (which may be embodied asa server), is operational with numerous other general purpose or specialpurpose computing system environments or configurations. Examples ofwell-known computing systems, environments, and/or configurations thatmay be suitable for use with the computer 1010 include, but are notlimited to, personal computer systems, server computer systems, thinclients, thick clients, hand-held or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

The computer 1010 may be described in the general context of computersystem-executable instructions, such as program modules, being executedby a computer system. Generally, program modules may include routines,programs, objects, components, logic, data structures, and so on thatperform particular tasks or implement particular abstract data types.

The computer 1010 may be practiced in a distributed cloud computingenvironment where tasks are performed by remote processing devices thatare linked through a communications network, generically referred to asa network 1100. In a distributed cloud computing environment, programmodules may be located in both local and remote computer system storagemedia including memory storage devices.

As shown in FIG. 5, the computer system 1000 and computer 1010 are shownin the form of a general-purpose computing device. The components of thecomputer 1010 may include, but are not limited to, one or moreprocessors or processing units 1020, a system memory 1030, and a bus1014 that couples various system components including system memory 1030to processor 1020.

The bus 1014 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

The computer 1010 typically includes a variety of computer readablemedia. Such media may be any available media that is accessible by thecomputer 1010 (e.g., computer system, or server), and can include bothvolatile and non-volatile media, as well as, removable and non-removablemedia.

Computer memory 1030 can include additional computer readable storagemedia 1034 in the form of volatile memory, such as random access memory(RAM) and/or cache memory 1038. The computer 1010 may further includeother removable/non-removable, volatile/non-volatile computer storagemedia, in one example, portable computer readable storage media 1072. Inone embodiment, a computer readable storage medium 1050 can be providedfor reading from and writing to a non-removable, non-volatile magneticmedia. The computer readable storage medium 1050 can be embodied, forexample, as a hard drive. Additional memory and data storage can beprovided, for example, as a storage system 1044 (e.g., a database) forstoring data 1048 and communicating with the processing unit 1020. Thedatabase can be stored on or part of a server 1040 Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 1014 by one or more datamedia interfaces. As will be further depicted and described below,memory 1030 may include at least one program product which can includeone or more program modules that are configured to carry out thefunctions of embodiments of the invention.

One or more computer programs can generically be referred to as aprogram 1060. The program 1060 can include program modules 1064, and maybe stored in memory 1030. By way of example, the memory 1030 may storean operating system 1052, an application program 1054, other programmodules, and program data. The program modules 1064 can generally carryout functions and/or methodologies of embodiments of the invention asdescribed herein. The one or more programs 1060 are stored in memory1030 and are executable by the processing unit 1020. It is understoodthat the operating system 1052 and application program 1054 stored onthe computer readable storage medium 1050 are similarly executable bythe processing unit 1020.

The computer 1010 may also communicate with one or more external devices1074 such as a keyboard, a pointing device, a display 1080, etc.; one ormore devices that enable a user to interact with the computer 1010;and/or any devices (e.g., network card, modem, etc.) that enables thecomputer 1010 to communicate with one or more other computing devices.Such communication can occur via Input/Output (I/O) interfaces 1022.Still yet, the computer 1010 can communicate with one or more networks1100 such as a local area network (LAN), a general wide area network(WAN), and/or a public network (e.g., the Internet) via networkadapter/interface 1026. As depicted, network adapter 1026 communicateswith the other components of the computer 1010 via bus 1014. It shouldbe understood that although not shown, other hardware and/or softwarecomponents could be used in conjunction with the computer 1010.Examples, include, but are not limited to: microcode, device drivers1024, redundant processing units, external disk drive arrays, RAIDsystems, tape drives, and data archival storage systems, etc.

The method 100 (FIG. 2) may be embodied in a program 1060 (FIG. 5)embodied on a computer readable storage device, for example, generallyreferred to as memory 1030, and can more specifically refer to computerreadable storage medium 1050, as shown in FIG. 5. The program 1060 isexecutable by the processor 1020 of the computer system 1010 (to executeprogram steps, code, or program code). Additional data storage may alsobe embodied as the database 1044 which includes data 1048. The programor executable instructions may be offered as a service by a provider.The computer 1010 and program 1060 shown in FIG. 5 are genericrepresentations of a computer and program that may be local to a user,or provided as a remote service (for example a cloud based service), andmay be provided in further examples, using a website accessible using anetwork 1100 (e.g., interacting with a network, the Internet, or cloudservices). It is understood that the computer 1010 and computer system1000 also generically represents herein a computer device or a computerincluded in a device, such as a laptop or desktop computer, etc., or oneor more servers, alone or as part of a datacenter. The computer andcomputer system can include the network adapter/interface 1026, and theinput/output (I/O) interface(s) 1022. The I/O interface 1022 allows forinput and output of data with an external device 1074 that may beconnected to the computer system. The network adapter/interface 1026 mayprovide communications between the computer system and a computernetwork generically shown as the network 1100. The method steps andsystem components and techniques may be embodied in modules of theprogram 1060 for performing the tasks of each of the steps of the methodand system, which are generically represented in FIG. 5 as programmodules 1064. The program 1060 and program modules 1064 can executespecific steps, routines, sub-routines, instructions or code, of theprogram. The method of the present disclosure can be run locally on adevice such as a mobile device, or can be run a service, for instance,on the server 1040 which may be remote and can be accessed using thecommunications network 1100.

It is understood that a computer or a program running on the computer1010 may communicate with a server, herein embodied as the server 1040,via one or more communications networks, herein embodied as the network1100. The communications network 1100 may include transmission media andnetwork links which include, for example, wireless, wired, or opticalfiber, and routers, firewalls, switches, and gateway computers. Thecommunications network may include connections, such as wire, wirelesscommunication links, or fiber optic cables. A communications network mayrepresent a worldwide collection of networks and gateways, such as theInternet, that use various protocols to communicate with one another,such as Lightweight Directory Access Protocol (LDAP), Transport ControlProtocol/Internet Protocol (TCP/IP), Hypertext Transport Protocol(HTTP), Wireless Application Protocol (WAP), etc. A network may alsoinclude a number of different types of networks, such as, for example,an intranet, a local area network (LAN), or a wide area network (WAN).

In one example, a computer can use a network which may access a websiteon the Web (World Wide Web) using the Internet. In one embodiment, acomputer, including a mobile device, can use a communications system ornetwork 1100 which can include the Internet, or a public switchedtelephone network (PSTN), for example, a cellular network. The PSTN mayinclude telephone lines, fiber optic cables, microwave transmissionlinks, cellular networks, and communications satellites. The Internetmay facilitate numerous searching and texting techniques, for example,using a cell phone or laptop computer to send queries to search enginesvia text messages (SMS), Multimedia Messaging Service (MMS) (related toSMS), email, or a web browser. The search engine can retrieve searchresults, that is, links to websites, documents, or other downloadabledata that correspond to the query, and similarly, provide the searchresults to the user via the device as, for example, a web page of searchresults.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

The invention claimed is:
 1. A system, comprising: a computer systemwhich comprises a computer processor, a non-transitory computer-readablestorage medium, and program instructions stored on the non-transitorycomputer-readable storage medium being executable by the computerprocessor, to cause the computer system to perform the programinstructions which comprise, receiving a data packet from a networksource and a network device, including network traffic on one or moreof: a fixed network, and a mobile network; extracting source anddestination data from the received data packet using a network collectorexecuting an algorithm, the extracting of source and destination datafrom the received data packet comprises extracting an IP source, asource port, an IP destination and a destination port from the receiveddata packet; determining a user from the extracted source anddestination data from the received data packet, the determining the userincluding extracting from a user data field in the data packet userinformation associated with the user via the network collector; creatinga label for the data packet, in response to a determination that thelabel does not exist for the extracted source and destination data fromthe received data packet, the label including the extracted source dataand historic source data for the determined user, the label includes thesource port and a vector comprising last used ports of the determineduser; calling a chaotic function using the network connector with thelabel for the received data packet, the calling of a chaotic functionwith the label for the received data packet comprises calling a Lorenzattractor function with the label for the received data packet; callingan alternative function for an output with the label for the receiveddata packet, and updating the label with output of the alternativefunction, in response to the chaotic function being returned false, and,in response to the chaotic function being returned false, the algorithmbeing run by the network collector analysing the network flow using oneor more of: pattern matching using ports, and IP addresses; capturingthe output of the chaotic function, in response to the chaotic functionbeing returned true, and updating the label with the output of thechaotic function; and the updating the label with the output of thechaotic function or with the output of the alternative functioncomprises, extending the vector with the source port and the output ofthe chaotic function or the output of the alternative function.